Physiological response parameters were assessed using mixed-effects linear models across species and treatments. Model selection was carried out using backward elimination of random-effects followed by fixed-effects using the package lmerTest (version 3.1.3)
While value ~ species + fpco2 + ftemp + (1 | colony) + species:ftemp was the best-fit model structure identified, we wanted to model both pCO2 and temperature responses by species so moving forward we are using the following model structure:
value ~ species * (fpco2 + ftemp) + (1 | colony)
Figure:
While value ~ species + ftemp was the best-fit model structure identified, we wanted to model responses with a random effect of colony so moving forward we are using the following model structure:
value ~ species * (fpco2 + ftemp) + (1 | colony)
Figure:
While value ~ species + ftemp + reef + species:ftemp + species:reef was the best-fit model structure identified, we wanted to model both pCO2 and temperature responses by species and with random effect of colony so moving forward we are using the following model structure:
value ~ species * (fpco2 + ftemp) + reef + species:reef + (1 | colony)
Figure:
While value ~ species + fpco2 + ftemp + reef + (1 | colony) + species:fpco2 + species:ftemp + fpco2:ftemp + species:reef + fpco2:reef + ftemp:reef + species:fpco2:ftemp + species:fpco2:reef + species:ftemp:reef + fpco2:ftemp:reef + species:fpco2:ftemp:reef was the best-fit model structure identified, we wanted to model both pCO2 and temperature responses by species and with random effect of colony so moving forward we are using the following model structure:
value ~ species * (fpco2 + ftemp) + reef + species:reef + (1 | colony)
Figure:
Since the best-fit model fits our design, we will proceed with the following model structure:
value ~ species + fpco2 + ftemp + reef + (1 | colony) + species:fpco2 + species:ftemp + fpco2:ftemp + species:reef
Figure:
Since the best-fit model fits our design, we will proceed with the following model structure:
value ~ species + fpco2 + ftemp + reef + (1 | colony) + species:fpco2 + species:ftemp + species:reef + fpco2:reef + species:fpco2:reef
Figure:
This is the same model from Bove et al 2019, just matching aesthetics for this manuscript.
Figure 1. Modeled 95% confidence interval of (A) total host energy reserves (mg cm-2), (B) cell density (106 cells cm-2), and (C) Chlorophyll a (ug cm-2) for S. siderea, P. strigosa, and P. astreoides at T0 (green) or T90 (red/blue), with individual coral fragment physiology denoted by points. Blue denotes 28°C and red denotes 31°C, with pCO2 treatment along the x axis.
Here, I am exploring the relationships between each physiology parameter measured above.
Figure 2. Correlation matrix for S. siderea, P. strigosa, and P. astreoides depicting pair-wise comparisons of physiological parameters within each species. Colour and ellipse width denote R2 of each significant comparison, and blank grids represent non-significant pair-wise comparisons (P > 0.05).Each parameter is denoted in blue text along the diagonal of each plot. Correlations with R2 above 0.5 (shown in orange and red in matrix plot) are explored further below.
## quartz_off_screen
## 2
## Permutation test for adonis under reduced model
## Marginal effects of terms
## Permutation: free
## Number of permutations: 2000
##
## adonis2(formula = sid_pca_df ~ fpco2 + ftemp + reef, data = s_df, permutations = bootnum, method = "eu", by = "margin")
## Df SumOfSqs R2 F Pr(>F)
## fpco2 3 145878 0.26441 11.1189 0.0004998 ***
## ftemp 1 25935 0.04701 5.9304 0.0039980 **
## reef 1 26681 0.04836 6.1009 0.0049975 **
## Residual 80 349861 0.63413
## Total 85 551720 1.00000
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Permutation test for adonis under reduced model
## Marginal effects of terms
## Permutation: free
## Number of permutations: 2000
##
## adonis2(formula = dip_pca_df ~ reef + fpco2 + ftemp, data = p_df, permutations = bootnum, method = "eu", by = "margin")
## Df SumOfSqs R2 F Pr(>F)
## reef 1 167951 0.08250 11.3347 0.0009995 ***
## fpco2 3 213070 0.10466 4.7932 0.0009995 ***
## ftemp 1 625389 0.30720 42.2061 0.0004998 ***
## Residual 71 1052041 0.51677
## Total 76 2035789 1.00000
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Permutation test for adonis under reduced model
## Marginal effects of terms
## Permutation: free
## Number of permutations: 2000
##
## adonis2(formula = por_pca_df ~ reef + ftemp + fpco2, data = a_df, permutations = bootnum, method = "eu", by = "margin")
## Df SumOfSqs R2 F Pr(>F)
## reef 1 969 0.00287 0.3246 0.7081459
## ftemp 1 52002 0.15388 17.4102 0.0004998 ***
## fpco2 3 96015 0.28412 10.7153 0.0004998 ***
## Residual 62 185186 0.54799
## Total 67 337935 1.00000
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Permutation test for adonis under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 2000
##
## adonis2(formula = s_df_sub[, c(14:17, 21:23, 29)] ~ fpco2 + fpco2:domSymb + domSymb + ftemp, data = s_df_sub, permutations = bootnum, method = "eu")
## Df SumOfSqs R2 F Pr(>F)
## fpco2 3 60040 0.26137 12.2655 0.0004998 ***
## domSymb 2 76699 0.33389 23.5033 0.0004998 ***
## ftemp 1 13933 0.06065 8.5391 0.0009995 ***
## fpco2:domSymb 6 28458 0.12389 2.9068 0.0009995 ***
## Residual 31 50582 0.22020
## Total 43 229711 1.00000
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## `summarise()` ungrouping output (override with `.groups` argument)
## # Comparison of Model Performance Indices
##
## Name | Model | AIC | BIC | R2 | R2 (adj.) | RMSE | Sigma | Performance-Score
## --------------------------------------------------------------------------------------------------
## ssid_dist_mod | lm | 166.373 | 182.595 | 0.229 | 0.173 | 0.668 | 0.697 | 99.97%
## ssid_dist_mod3 | lm | 170.343 | 184.248 | 0.165 | 0.117 | 0.695 | 0.720 | 73.96%
## ssid_dist_mod2 | lm | 271.007 | 287.229 | 0.229 | 0.173 | 1.342 | 1.400 | 37.84%
## ssid_dist_mod4 | lm | 276.960 | 290.865 | 0.143 | 0.094 | 1.415 | 1.465 | 0.00%
##
## Call:
## lm(formula = log(dist) ~ fpco2 + ftemp + reef, data = sid_dist)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.08433 -0.28862 0.01186 0.32752 1.47527
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.565379 0.197374 2.865 0.00553 **
## fpco2420 -0.005195 0.288633 -0.018 0.98569
## fpco2680 -0.034515 0.223226 -0.155 0.87757
## fpco23300 0.659994 0.221422 2.981 0.00397 **
## ftemp31 0.055395 0.175208 0.316 0.75283
## reefN -0.386667 0.161708 -2.391 0.01953 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6967 on 69 degrees of freedom
## Multiple R-squared: 0.2288, Adjusted R-squared: 0.1729
## F-statistic: 4.095 on 5 and 69 DF, p-value: 0.002585
## Loading required namespace: qqplotr
## `geom_smooth()` using formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## `summarise()` regrouping output by 'treat_plot' (override with `.groups` argument)
## `summarise()` ungrouping output (override with `.groups` argument)
## # Comparison of Model Performance Indices
##
## Name | Model | AIC | BIC | R2 | R2 (adj.) | RMSE | Sigma | Performance-Score
## --------------------------------------------------------------------------------------------------
## pstr_dist_mod2 | lm | 151.079 | 185.229 | 0.233 | 0.061 | 0.561 | 0.625 | 70.34%
## pstr_dist_mod4 | lm | 148.080 | 166.293 | 0.106 | 0.024 | 0.605 | 0.637 | 66.85%
## pstr_dist_mod3 | lm | 149.721 | 170.211 | 0.111 | 0.014 | 0.604 | 0.641 | 53.71%
## pstr_dist_mod | lm | 151.928 | 167.865 | 0.031 | -0.043 | 0.631 | 0.659 | 15.28%
##
## Call:
## lm(formula = log(dist) ~ fpco2 * ftemp * reef, data = dip_dist)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.47623 -0.38430 -0.05872 0.37259 1.46982
##
## Coefficients: (2 not defined because of singularities)
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.475309 0.197643 2.405 0.01939 *
## fpco2420 0.194384 0.456437 0.426 0.67178
## fpco2680 0.119971 0.296465 0.405 0.68721
## fpco23300 -0.170264 0.287169 -0.593 0.55555
## ftemp31 0.310618 0.342328 0.907 0.36797
## reefN 0.878481 0.322750 2.722 0.00856 **
## fpco2420:ftemp31 NA NA NA NA
## fpco2680:ftemp31 -0.469504 0.544266 -0.863 0.39189
## fpco23300:ftemp31 0.473575 0.488587 0.969 0.33643
## fpco2420:reefN 0.006716 0.708029 0.009 0.99246
## fpco2680:reefN -0.836043 0.467012 -1.790 0.07864 .
## fpco23300:reefN -0.831141 0.461167 -1.802 0.07670 .
## ftemp31:reefN -1.303040 0.529103 -2.463 0.01678 *
## fpco2420:ftemp31:reefN NA NA NA NA
## fpco2680:ftemp31:reefN 1.248932 0.848178 1.472 0.14630
## fpco23300:ftemp31:reefN 0.911877 0.772523 1.180 0.24266
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.625 on 58 degrees of freedom
## Multiple R-squared: 0.233, Adjusted R-squared: 0.0611
## F-statistic: 1.355 on 13 and 58 DF, p-value: 0.2093
## `geom_smooth()` using formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## `summarise()` regrouping output by 'treat_plot' (override with `.groups` argument)
## `summarise()` ungrouping output (override with `.groups` argument)
## # Comparison of Model Performance Indices
##
## Name | Model | AIC | BIC | R2 | R2 (adj.) | RMSE | Sigma | Performance-Score
## --------------------------------------------------------------------------------------------------
## past_dist_mod5 | lm | 106.292 | 118.550 | 0.065 | -0.007 | 0.553 | 0.579 | 79.27%
## past_dist_mod3 | lm | 111.283 | 129.671 | 0.082 | -0.050 | 0.548 | 0.592 | 76.77%
## past_dist_mod | lm | 119.162 | 147.765 | 0.115 | -0.126 | 0.538 | 0.613 | 74.33%
## past_dist_mod2 | lm | 119.162 | 147.765 | 0.115 | -0.126 | 0.538 | 0.613 | 74.33%
## past_dist_mod4 | lm | 192.303 | 204.562 | 0.096 | 0.027 | 1.177 | 1.232 | 27.11%
##
## Call:
## lm(formula = log(dist) ~ fpco2 + ftemp, data = por_dist)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.6110 -0.3076 0.1067 0.3932 1.1107
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.56933 0.15308 3.719 0.000491 ***
## fpco2420 -0.20237 0.29678 -0.682 0.498332
## fpco2680 0.04701 0.19656 0.239 0.811918
## fpco23300 0.17055 0.20256 0.842 0.403651
## ftemp31 0.30038 0.17213 1.745 0.086883 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5793 on 52 degrees of freedom
## Multiple R-squared: 0.06514, Adjusted R-squared: -0.006773
## F-statistic: 0.9058 on 4 and 52 DF, p-value: 0.4675
## `geom_smooth()` using formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## `summarise()` regrouping output by 'treat_plot' (override with `.groups` argument)
| treatment | N | mean | lower 95% | upper 95% |
|---|---|---|---|---|
| (a) SSID | ||||
| 300_28 | 11 | 0.54 | 0.47 | 0.60 |
| 300_31 | 9 | 0.48 | 0.41 | 0.55 |
| 3300_28 | 12 | 0.43 | 0.37 | 0.50 |
| 3300_31 | 12 | 0.38 | 0.31 | 0.44 |
| 420_28 | 12 | 0.50 | 0.43 | 0.57 |
| 420_31 | 12 | 0.45 | 0.38 | 0.51 |
| 680_28 | 13 | 0.46 | 0.39 | 0.53 |
| 680_31 | 12 | 0.40 | 0.34 | 0.47 |
| (b) PSTR | ||||
| 300_28 | 16 | 0.53 | 0.47 | 0.59 |
| 300_31 | 9 | 0.27 | 0.19 | 0.35 |
| 3300_28 | 16 | 0.43 | 0.36 | 0.49 |
| 3300_31 | 8 | 0.17 | 0.09 | 0.24 |
| 420_28 | 5 | 0.49 | 0.42 | 0.56 |
| 420_31 | 6 | 0.23 | 0.15 | 0.32 |
| 680_28 | 14 | 0.45 | 0.39 | 0.51 |
| 680_31 | 5 | 0.19 | 0.11 | 0.28 |
| (c) PAST | ||||
| 300_28 | 11 | 0.23 | 0.17 | 0.30 |
| 300_31 | 6 | 0.19 | 0.10 | 0.27 |
| 3300_28 | 12 | 0.13 | 0.06 | 0.20 |
| 3300_31 | 4 | 0.08 | 0.00 | 0.17 |
| 420_28 | 12 | 0.20 | 0.13 | 0.26 |
| 420_31 | 7 | 0.15 | 0.07 | 0.23 |
| 680_28 | 10 | 0.16 | 0.09 | 0.22 |
| 680_31 | 9 | 0.11 | 0.03 | 0.19 |
| treatment | N | mean | lower 95% | upper 95% |
|---|---|---|---|---|
| (a) SSID | ||||
| 300_28 | 11 | 0.37 | 0.30 | 0.44 |
| 300_31 | 9 | 0.35 | 0.28 | 0.42 |
| 3300_28 | 12 | 0.37 | 0.30 | 0.44 |
| 3300_31 | 12 | 0.35 | 0.28 | 0.42 |
| 420_28 | 12 | 0.37 | 0.30 | 0.44 |
| 420_31 | 12 | 0.35 | 0.27 | 0.42 |
| 680_28 | 13 | 0.38 | 0.31 | 0.45 |
| 680_31 | 12 | 0.36 | 0.29 | 0.43 |
| (b) PSTR | ||||
| 300_28 | 16 | 0.24 | 0.17 | 0.31 |
| 300_31 | 9 | 0.11 | 0.02 | 0.20 |
| 3300_28 | 15 | 0.24 | 0.17 | 0.31 |
| 3300_31 | 8 | 0.10 | 0.02 | 0.19 |
| 420_28 | 5 | 0.24 | 0.17 | 0.31 |
| 420_31 | 5 | 0.11 | 0.02 | 0.20 |
| 680_28 | 14 | 0.24 | 0.17 | 0.31 |
| 680_31 | 5 | 0.11 | 0.02 | 0.20 |
| (c) PAST | ||||
| 300_28 | 11 | 0.15 | 0.08 | 0.23 |
| 300_31 | 6 | 0.20 | 0.11 | 0.29 |
| 3300_28 | 12 | 0.16 | 0.08 | 0.23 |
| 3300_31 | 4 | 0.22 | 0.14 | 0.31 |
| 420_28 | 12 | 0.16 | 0.08 | 0.23 |
| 420_31 | 7 | 0.20 | 0.11 | 0.29 |
| 680_28 | 10 | 0.16 | 0.08 | 0.23 |
| 680_31 | 9 | 0.20 | 0.11 | 0.29 |
| treatment | N | mean | lower 95% | upper 95% |
|---|---|---|---|---|
| (a) SSID | ||||
| 300_28 | 11 | 1.15 | 0.95 | 1.35 |
| 300_31 | 8 | 0.82 | 0.61 | 1.02 |
| 3300_28 | 12 | 1.10 | 0.91 | 1.29 |
| 3300_31 | 12 | 0.77 | 0.60 | 0.96 |
| 420_28 | 12 | 1.08 | 0.90 | 1.26 |
| 420_31 | 12 | 0.75 | 0.57 | 0.94 |
| 680_28 | 13 | 1.27 | 1.10 | 1.45 |
| 680_31 | 12 | 0.94 | 0.75 | 1.11 |
| (b) PSTR | ||||
| 300_28 | 16 | 0.77 | 0.60 | 0.93 |
| 300_31 | 9 | 0.50 | 0.30 | 0.68 |
| 3300_28 | 16 | 0.62 | 0.45 | 0.78 |
| 3300_31 | 8 | 0.34 | 0.15 | 0.55 |
| 420_28 | 5 | 0.67 | 0.41 | 0.92 |
| 420_31 | 6 | 0.40 | 0.16 | 0.65 |
| 680_28 | 14 | 0.56 | 0.37 | 0.75 |
| 680_31 | 7 | 0.29 | 0.07 | 0.51 |
| (c) PAST | ||||
| 300_28 | 11 | 0.82 | 0.61 | 1.03 |
| 300_31 | 6 | 0.65 | 0.41 | 0.88 |
| 3300_28 | 12 | 0.58 | 0.38 | 0.78 |
| 3300_31 | 4 | 0.41 | 0.16 | 0.65 |
| 420_28 | 12 | 0.90 | 0.71 | 1.10 |
| 420_31 | 7 | 0.73 | 0.51 | 0.95 |
| 680_28 | 10 | 0.61 | 0.41 | 0.81 |
| 680_31 | 9 | 0.43 | 0.23 | 0.64 |
| treatment | N | mean | lower 95% | upper 95% |
|---|---|---|---|---|
| (a) SSID | ||||
| 300_28 | 11 | 3.32 | 2.23 | 4.46 |
| 300_31 | 9 | 2.45 | 1.33 | 3.58 |
| 3300_28 | 12 | 2.04 | 0.97 | 3.07 |
| 3300_31 | 12 | 1.18 | 0.12 | 2.23 |
| 420_28 | 12 | 3.48 | 2.42 | 4.50 |
| 420_31 | 12 | 2.61 | 1.55 | 3.67 |
| 680_28 | 13 | 2.96 | 1.95 | 3.98 |
| 680_31 | 12 | 2.10 | 1.04 | 3.14 |
| (b) PSTR | ||||
| 300_28 | 16 | 2.16 | 1.14 | 3.15 |
| 300_31 | 9 | 0.42 | -0.77 | 1.60 |
| 3300_28 | 16 | 1.53 | 0.53 | 2.52 |
| 3300_31 | 8 | -0.27 | -1.48 | 0.89 |
| 420_28 | 5 | 2.16 | 0.75 | 3.61 |
| 420_31 | 6 | 0.45 | -0.96 | 1.86 |
| 680_28 | 14 | 1.71 | 0.68 | 2.75 |
| 680_31 | 7 | -0.09 | -1.30 | 1.14 |
| (c) PAST | ||||
| 300_28 | 11 | 7.29 | 6.13 | 8.48 |
| 300_31 | 6 | 6.42 | 5.02 | 7.74 |
| 3300_28 | 12 | 5.92 | 4.74 | 7.16 |
| 3300_31 | 4 | 4.86 | 3.51 | 6.15 |
| 420_28 | 12 | 6.43 | 5.28 | 7.57 |
| 420_31 | 6 | 5.51 | 4.22 | 6.83 |
| 680_28 | 10 | 5.09 | 3.84 | 6.35 |
| 680_31 | 8 | 4.19 | 2.87 | 5.45 |
| treatment | N | mean | lower 95% | upper 95% |
|---|---|---|---|---|
| (a) SSID | ||||
| 300_28 | 11 | 112.38 | 81.74 | 143.62 |
| 300_31 | 9 | 105.47 | 71.18 | 140.02 |
| 3300_28 | 12 | 48.52 | 17.15 | 79.21 |
| 3300_31 | 12 | 32.61 | 3.07 | 63.16 |
| 420_28 | 12 | 155.21 | 122.77 | 186.81 |
| 420_31 | 12 | 77.84 | 46.62 | 108.58 |
| 680_28 | 13 | 83.24 | 53.49 | 114.40 |
| 680_31 | 12 | 82.41 | 51.78 | 113.66 |
| (b) PSTR | ||||
| 300_28 | 16 | 185.93 | 157.24 | 214.55 |
| 300_31 | 9 | 120.37 | 85.65 | 154.64 |
| 3300_28 | 16 | 78.53 | 51.36 | 106.93 |
| 3300_31 | 8 | -1.42 | -37.11 | 34.23 |
| 420_28 | 5 | 161.17 | 118.71 | 202.49 |
| 420_31 | 6 | 26.74 | -14.58 | 66.79 |
| 680_28 | 14 | 84.10 | 54.62 | 114.41 |
| 680_31 | 5 | 17.96 | -22.30 | 58.03 |
| (c) PAST | ||||
| 300_28 | 11 | 97.02 | 63.84 | 130.54 |
| 300_31 | 6 | 155.01 | 116.85 | 192.29 |
| 3300_28 | 12 | 15.56 | -18.42 | 45.96 |
| 3300_31 | 4 | 61.04 | 19.29 | 101.45 |
| 420_28 | 12 | 64.66 | 33.23 | 97.25 |
| 420_31 | 7 | 51.82 | 15.19 | 89.83 |
| 680_28 | 10 | 33.69 | 1.31 | 67.61 |
| 680_31 | 9 | 96.83 | 62.24 | 133.28 |
| treatment | N | mean | lower 95% | upper 95% |
|---|---|---|---|---|
| (a) SSID | ||||
| 300_28 | 11 | 2.02 | 1.61 | 2.43 |
| 300_31 | 8 | 1.62 | 1.21 | 2.04 |
| 3300_28 | 12 | 1.92 | 1.56 | 2.28 |
| 3300_31 | 12 | 1.53 | 1.17 | 1.89 |
| 420_28 | 12 | 2.02 | 1.65 | 2.40 |
| 420_31 | 12 | 1.58 | 1.21 | 1.95 |
| 680_28 | 13 | 2.06 | 1.70 | 2.41 |
| 680_31 | 12 | 1.65 | 1.29 | 2.01 |
| (b) PSTR | ||||
| 300_28 | 16 | 1.60 | 1.25 | 1.94 |
| 300_31 | 9 | 0.96 | 0.58 | 1.35 |
| 3300_28 | 15 | 1.28 | 0.92 | 1.64 |
| 3300_31 | 8 | 0.60 | 0.20 | 0.99 |
| 420_28 | 5 | 1.39 | 0.84 | 1.94 |
| 420_31 | 5 | 0.71 | 0.14 | 1.27 |
| 680_28 | 14 | 1.23 | 0.82 | 1.62 |
| 680_31 | 5 | 0.56 | 0.11 | 1.00 |
| (c) PAST | ||||
| 300_28 | 11 | 1.26 | 0.84 | 1.69 |
| 300_31 | 6 | 1.12 | 0.65 | 1.60 |
| 3300_28 | 12 | 0.86 | 0.41 | 1.29 |
| 3300_31 | 4 | 0.56 | 0.13 | 0.98 |
| 420_28 | 12 | 1.26 | 0.86 | 1.66 |
| 420_31 | 7 | 1.14 | 0.71 | 1.58 |
| 680_28 | 10 | 0.85 | 0.44 | 1.25 |
| 680_31 | 9 | 0.72 | 0.31 | 1.14 |
Session information from the last run date on 2021-04-05:
## R version 3.6.3 (2020-02-29)
## Platform: x86_64-apple-darwin15.6.0 (64-bit)
## Running under: macOS Catalina 10.15.7
##
## Matrix products: default
## BLAS: /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRblas.0.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRlapack.dylib
##
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
##
## attached base packages:
## [1] grid stats graphics grDevices utils datasets methods
## [8] base
##
## other attached packages:
## [1] png_0.1-7 MASS_7.3-53 performance_0.7.0 wesanderson_0.3.6
## [5] RColorBrewer_1.1-2 gridGraphics_0.5-1 corrplot_0.84 Hmisc_4.4-2
## [9] Formula_1.2-4 survival_3.2-7 magick_2.5.2 ggpubr_0.4.0
## [13] vroom_1.3.2 lmerTest_3.1-3 lme4_1.1-26 Matrix_1.3-2
## [17] kableExtra_1.3.1 ggfortify_0.4.11 cowplot_1.1.1 Rmisc_1.5
## [21] shiny_1.5.0 vegan_2.5-7 lattice_0.20-41 permute_0.9-5
## [25] forcats_0.5.0 stringr_1.4.0 purrr_0.3.4 tibble_3.0.4
## [29] tidyverse_1.3.0 plotly_4.9.3 openxlsx_4.2.3 tidyr_1.1.2
## [33] ggbiplot_0.55 scales_1.1.1 plyr_1.8.6 dplyr_1.0.2
## [37] ggplot2_3.3.3 readr_1.4.0 knitr_1.30
##
## loaded via a namespace (and not attached):
## [1] readxl_1.3.1 backports_1.2.1 lazyeval_0.2.2
## [4] splines_3.6.3 qqplotr_0.0.4 digest_0.6.27
## [7] htmltools_0.5.1 fansi_0.4.1 magrittr_2.0.1
## [10] checkmate_2.0.0 cluster_2.1.0 see_0.6.2
## [13] modelr_0.1.8 jpeg_0.1-8.1 colorspace_2.0-0
## [16] rvest_0.3.6 ggrepel_0.9.0 haven_2.3.1
## [19] xfun_0.20 crayon_1.3.4 jsonlite_1.7.2
## [22] glue_1.4.2 gtable_0.3.0 webshot_0.5.2
## [25] car_3.0-10 DEoptimR_1.0-8 abind_1.4-5
## [28] DBI_1.1.0 rstatix_0.6.0 Rcpp_1.0.5
## [31] viridisLite_0.3.0 xtable_1.8-4 htmlTable_2.1.0
## [34] foreign_0.8-75 bit_4.0.4 htmlwidgets_1.5.3
## [37] httr_1.4.2 ellipsis_0.3.1 pkgconfig_2.0.3
## [40] farver_2.0.3 nnet_7.3-14 dbplyr_2.0.0
## [43] tidyselect_1.1.0 labeling_0.4.2 rlang_0.4.10
## [46] later_1.1.0.1 effectsize_0.4.1 munsell_0.5.0
## [49] cellranger_1.1.0 tools_3.6.3 cli_2.2.0
## [52] generics_0.1.0 broom_0.7.3 ggridges_0.5.3
## [55] evaluate_0.14 fastmap_1.0.1 yaml_2.2.1
## [58] bit64_4.0.5 fs_1.5.0 robustbase_0.93-7
## [61] zip_2.1.1 nlme_3.1-151 mime_0.9
## [64] xml2_1.3.2 compiler_3.6.3 rstudioapi_0.13
## [67] curl_4.3 ggsignif_0.6.0 reprex_0.3.0
## [70] statmod_1.4.35 stringi_1.5.3 highr_0.8
## [73] parameters_0.10.1 nloptr_1.2.2.2 vctrs_0.3.6
## [76] pillar_1.4.7 lifecycle_0.2.0 data.table_1.13.6
## [79] insight_0.13.1 httpuv_1.5.5 R6_2.5.0
## [82] latticeExtra_0.6-29 promises_1.1.1 gridExtra_2.3
## [85] rio_0.5.16 boot_1.3-25 assertthat_0.2.1
## [88] withr_2.3.0 mgcv_1.8-33 bayestestR_0.8.0
## [91] parallel_3.6.3 hms_1.0.0 rpart_4.1-15
## [94] minqa_1.2.4 rmarkdown_2.6 carData_3.0-4
## [97] numDeriv_2016.8-1.1 lubridate_1.7.9.2 base64enc_0.1-3